Relevance of Artificial Intelligence-Assisted Echocardiography for Left Ventricular Ejection Fraction Assessment in Geriatric Patients

NCT07701369 | Recruiting

• 1 other identifier: 2025-A02039-40
• Study Type: interventional
• Target: 130
• Locations: 1 country
• Sites: 1

Brief Summary

Heart failure (HF) is the leading cause of hospitalization among adults aged 80 years and older and represents a major diagnostic challenge in geriatric medicine due to frequently atypical clinical presentations and the presence of multiple comorbidities. Although transthoracic echocardiography (TTE) with measurement of left ventricular ejection fraction (LVEF) remains the gold standard for cardiac functional assessment, access to echocardiography is often limited in geriatric wards. Recent advances in artificial intelligence (AI) have enabled the development of portable ultrasound devices and automated image analysis software capable of providing reliable and reproducible LVEF measurements. AI-assisted automated LVEF assessment (AutoEF-AI) may therefore represent a valuable alternative to conventional echocardiography for the cardiac evaluation of older patients with heart failure.

Conditions

Heart Failure

Keywords

Heart failure; Artificial Intelligence-Assisted Echocardiography; Artificial Intelligence; Echocardiography; Left Ventricular Ejection Fraction

Outcome Measures

Primary Outcomes (1)

• Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography.

  Agreement will be assessed using: * Intraclass Correlation Coefficient (ICC) * Spearman correlation coefficient * Bland-Altman analysis * Weighted kappa coefficient for the classification of patients according to LVEF categories (≤40%, 41-49%, and ≥50%)

  At baseline

Secondary Outcomes (3)

• Diagnostic performance of AutoEF-AI for the detection of LVEF <50%, including sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy.

  At baseline

• Analysis of factors associated with agreement between the two methods

  At baseline

• Feasibility of AutoEF-AI use by a geriatrician after a short training program

  At baseline

Study Arms (2)

Standard Echocardiography (Reference method)

OTHER

The standard echocardiography will be performed by a cardiologist as part of routine clinical care.

Diagnostic Test: Standard Echocardiography (Reference method)

AutoEF-AI Assessment

EXPERIMENTAL

AI-assisted automated LVEF assessment

Diagnostic Test: AutoEF-AI Assessment

Interventions

AutoEF-AI Assessment DIAGNOSTIC_TEST

Performed by a geriatrician who has completed a one-day practical training session and combines: * A handheld ultrasound device providing real-time image acquisition guidance for obtaining apical views. * Us2.ai software for automated LVEF analysis. The geriatrician is blinded to results of the gold standard echocardiography performed by the cardiologist.

AutoEF-AI Assessment

Standard Echocardiography (Reference method) DIAGNOSTIC_TEST

The standard echocardiography will be performed by an expert cardiologist as part of routine clinical care and will serve as the gold standard

Standard Echocardiography (Reference method)

Eligibility Criteria

• Age: 75 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)

You may qualify if:

• Age ≥75 years.
• Hospitalization in a geriatric unit for acute heart failure according to the 2021 ESC diagnostic criteria.
• Hemodynamic stability at the time of echocardiographic examination.
• Ability to understand study information, provide written informed consent, and willingness to participate.
• Affiliation with, or beneficiary of, a health insurance/social security scheme.

You may not qualify if:

• Hemodynamic instability preventing echocardiographic assessment.
• Contraindication to transthoracic echocardiography.
• Patients under legal protection (guardianship, curatorship, or judicial protection measures) or unable to provide informed consent.
• Refusal to participate in the study.

Sponsors & Collaborators

• Gérond'if: lead

Study Sites (1)

Broca Hospital

Paris, 75013, France

RECRUITING

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Study Officials

• Olivier HANON, MD PhD

  Geriatric Department, Broca hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Isabelle DUFOUR

CONTACT

+33 (0) 185781011; isabelle.dufour@gerondif.org

Prisca LUCAS, PhD MPH

CONTACT

+33 (0)185737323; prisca.lucas@gerondif.org

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: SINGLE
• Who Masked: INVESTIGATOR
• Purpose: DIAGNOSTIC
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography

Study Record Dates

• First Submitted: July 1, 2026
• First Posted: July 14, 2026
• Study Start: July 7, 2026
• Primary Completion (Estimated): June 30, 2028
• Study Completion (Estimated): June 30, 2028
• Last Updated: July 28, 2026

Record last verified: 2026-07

Locations

FR (1)